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Speed Trajectory Tracking of A Robotic Fish Based on Iterative Learning Control Approach

机译:基于迭代学习控制方法的机器人鱼类速度轨迹跟踪

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摘要

In this paper, a novel work is presented, where iterative learning control (ILC) approach is applied to a precise speed control approach for a two-link robotic fish. First, by virtue of the Lagrangian mechanics method, we establish a mathematical model for the two-link carangiform robotic fish, which is highly nonlinear and non-affine in control input. According to the structure of the constructed dynamical model, a P-type iterative learning control (ILC) algorithm is proposed for speed tracking tasks of the robotic fish. The convergence analysis of the proposed controller is derived based on composite energy function (CEF). Moreover, its efficiency is not only illustrated by simulations, but also verified through experimental results. It is shown that ILC is an effective control approach for the motion control of robotic fish because of its model-free property and the simplicity of the algorithm.
机译:本文提出了一种新颖的工作,其中迭代学习控制(ILC)方法适用于两连杆机器人鱼的精确速度控制方法。首先,凭借拉格朗日力学方法,我们建立了双连杆碳状机器人鱼类的数学模型,其对控制输入具有高度非线性和非仿射。根据构造动力学模型的结构,提出了一种用于机器人鱼的速度跟踪任务的p型迭代学习控制(ILC)算法。基于复合能量函数(CEF)导出所提出的控制器的收敛性分析。此外,其效率不仅通过模拟说明,而且通过实验结果验证。结果表明,由于其型号的性能和算法的简单性,ILC是机器人鱼类运动控制的有效控制方法。

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